A low complexity lossless compression scheme for wearable ECG sensors

This paper presents a low complexity lossless ECG compression algorithm for data reduction in wireless ambulatory ECG sensors. The proposed algorithm uses a novel linear prediction technique for redundancy removal and a joint coding-packaging scheme for compaction of the residual prediction error. Multiple linear predictors are engaged simultaneously to track the incoming data and the best prediction estimate is adaptively chosen based on the temporal signal characteristics to minimize error. An improved dynamic coding-packaging scheme frames the resulting estimation error into fixed-length 16-bit format. The proposed technique achieves an average compression ratio of 2.38× on MIT/BIH ECG database. Low complexity and good compression performance makes the proposed technique suitable for wearable ambulatory ECG monitoring applications.